Universiti Teknologi Malaysia Institutional Repository

Die defect classification using image processing

Maniam, Darmadevaindra (2015) Die defect classification using image processing. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering.

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Abstract

This work presents die defect classification using image processing. The detection of the flaw is based on the defect features in the die. Each unique defect or feature structure is defined from samples that has been collected by Visual Inspection Inspectors. The defects are then grouped into user definition categories such as blob, pin hole, underfill and die crack.This work also describes the image processing algorithms utilized to perform defect classification. The defect classification was developed from MATLAB program.It is aimed at locating the Region of Interest of the die from the image and extract it. The extracted image is then used to classify or recognize the specific classification category of the defect.Total samples that is being used in this project is 67 die samples. The results obtained from this work shows the overall accuracy of 94% for die defect detection and 87% for defect classification.

Item Type:Thesis (Masters)
Additional Information:Thesis (Sarjana Kejuruteraan (Elektrik - Komputer dan Sistem Mikroelektronik)) - Universiti Teknologi Malaysia, 2015; Supervisor : Dr. Usman Ullah Sheikh
Uncontrolled Keywords:die defect classification, image processing
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:53921
Deposited By: Fazli Masari
Deposited On:06 Apr 2016 07:21
Last Modified:08 Oct 2020 03:32

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